A mechanism study of acid-assisted oxidative stabilization of asphaltene-derived carbon fibers
Bibliographic record
Abstract
The development of inexpensive carbon fiber precursors is necessary to meet the future demands of carbon fibers. This work shows how asphaltenes, which are obtained as a by-product in bitumen production, can play an important role as such inexpensive carbon fiber precursors. To synthesize carbon fibers from asphaltene, stabilization by means of oxidizing acids (HNO3 and H2SO4) was developed. Stabilization could not be achieved by a non-oxidizing acid (HCl). The reactions leading to fiber stabilization was investigated for nitric acid treatment, which led to oxidation and the incorporation of nitro-groups. Further thermal treatment caused an increase in C/H ratio that was related to decomposition of nitro-groups, which facilitated air oxidation and other reactions leading to the loss of volatile hydrogen-rich products, such as light hydrocarbons. Additionally, the influence of the acid concentration during treatment on fiber properties, such as fiber diameter, composition, tensile strength and elastic modulus, has been examined. The application of the acid treatment leads to carbon fibers with good tensile properties, with a tensile strength and elastic modulus of 811 MPa and 32.7 GPa, respectively. The overall yield of carbon fibers is 37 – 38 wt.%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".